from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
reporting = HpMatchReporting(against_lib="onnx", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time onnx. For instance, a speedup of 2 means that onnx is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | ... | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | e70d8e7886766d41f30889506baa1e67 | 2cf49829391aa7891e877f2ed070adf0 | 1.944462 | 0.149903 | NaN | ... | brute | -1 | 1 | 0.663 | 0.309275 | 0.007307 | 1.000 | 6.287163 | 6.288918 | 0.337 |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | e70d8e7886766d41f30889506baa1e67 | 2cf49829391aa7891e877f2ed070adf0 | 0.024074 | 0.003250 | NaN | ... | brute | -1 | 1 | 1.000 | 17.004475 | 0.195576 | 0.757 | 0.001416 | 0.001416 | 0.243 |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 22d5eac4a4146149b35eae6914921514 | 2cf49829391aa7891e877f2ed070adf0 | 2.760593 | 0.035551 | NaN | ... | brute | -1 | 5 | 0.757 | 16.894082 | 0.018520 | 0.882 | 0.163406 | 0.163406 | 0.125 |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 16f94fc93942ff7ece860c9b0f64645f | 2cf49829391aa7891e877f2ed070adf0 | 2.031129 | 0.008811 | NaN | ... | brute | 1 | 100 | 0.882 | 0.315060 | 0.005282 | 1.000 | 6.446805 | 6.447711 | 0.118 |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 16f94fc93942ff7ece860c9b0f64645f | 2cf49829391aa7891e877f2ed070adf0 | 0.020564 | 0.000214 | NaN | ... | brute | 1 | 100 | 1.000 | 16.962261 | 0.037067 | 0.757 | 0.001212 | 0.001212 | 0.243 |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2d5f2b2c02d77766434d9e5033b4a76c | 2cf49829391aa7891e877f2ed070adf0 | 2.763092 | 0.032432 | NaN | ... | brute | -1 | 100 | 0.882 | 16.914865 | 0.018723 | 0.663 | 0.163353 | 0.163353 | 0.219 |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | efac583623711d395ddae7a1e881ff68 | 2cf49829391aa7891e877f2ed070adf0 | 2.010532 | 0.001644 | NaN | ... | brute | 1 | 5 | 0.757 | 0.239383 | 0.004843 | 1.000 | 8.398792 | 8.400510 | 0.243 |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | efac583623711d395ddae7a1e881ff68 | 2cf49829391aa7891e877f2ed070adf0 | 0.020597 | 0.000252 | NaN | ... | brute | 1 | 5 | 1.000 | 3.714115 | 0.011594 | 0.922 | 0.005546 | 0.005546 | 0.078 |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | b79d63bb7670c492de5c3befac58fe29 | 2cf49829391aa7891e877f2ed070adf0 | 1.161442 | 0.009139 | NaN | ... | brute | 1 | 1 | 0.663 | 3.759380 | 0.006443 | 0.929 | 0.308945 | 0.308946 | 0.266 |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | e70d8e7886766d41f30889506baa1e67 | 88843f54689e3271092f70126e1de585 | 1.732155 | 0.015052 | NaN | ... | brute | -1 | 1 | 0.896 | 0.239641 | 0.004121 | 1.000 | 7.228124 | 7.229193 | 0.104 |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | e70d8e7886766d41f30889506baa1e67 | 88843f54689e3271092f70126e1de585 | 0.004219 | 0.001883 | NaN | ... | brute | -1 | 1 | 1.000 | 3.727263 | 0.022320 | 0.922 | 0.001132 | 0.001132 | 0.078 |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 22d5eac4a4146149b35eae6914921514 | 88843f54689e3271092f70126e1de585 | 2.637346 | 0.019484 | NaN | ... | brute | -1 | 5 | 0.922 | 3.774008 | 0.017433 | 0.896 | 0.698818 | 0.698826 | 0.026 |
12 rows × 22 columns
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.052 | 0.0 | -1 | 1 | 17.099 | 0.135 | 0.663 | 0.001 | 0.001 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.057 | 0.0 | -1 | 5 | 0.314 | 0.005 | 1.000 | 0.036 | 0.036 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.007 | 0.0 | 1 | 100 | 16.989 | 0.018 | 0.882 | 0.001 | 0.001 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.014 | 0.0 | -1 | 100 | 0.316 | 0.005 | 1.000 | 0.036 | 0.036 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.004 | 6.127 | 0.0 | 1 | 5 | 3.768 | 0.012 | 0.896 | 0.003 | 0.003 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.028 | 0.0 | 1 | 1 | 0.239 | 0.004 | 1.000 | 0.048 | 0.048 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.377 | 0.0 | -1 | 1 | 3.761 | 0.012 | 0.929 | 0.001 | 0.001 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.379 | 0.0 | -1 | 5 | 0.237 | 0.003 | 1.000 | 0.018 | 0.018 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.944 | 0.150 | 0.000 | 0.002 | -1 | 1 | 0.309 | 0.007 | 1.000 | 6.287 | 6.289 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.024 | 0.003 | 0.000 | 0.024 | -1 | 1 | 17.004 | 0.196 | 0.757 | 0.001 | 0.001 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.761 | 0.036 | 0.000 | 0.003 | -1 | 5 | 16.894 | 0.019 | 0.882 | 0.163 | 0.163 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.002 | 0.000 | 0.023 | -1 | 5 | 0.315 | 0.006 | 1.000 | 0.074 | 0.074 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.031 | 0.009 | 0.000 | 0.002 | 1 | 100 | 0.315 | 0.005 | 1.000 | 6.447 | 6.448 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.021 | 0.000 | 0.000 | 0.021 | 1 | 100 | 16.962 | 0.037 | 0.757 | 0.001 | 0.001 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.763 | 0.032 | 0.000 | 0.003 | -1 | 100 | 16.915 | 0.019 | 0.663 | 0.163 | 0.163 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.003 | 0.000 | 0.025 | -1 | 100 | 0.306 | 0.005 | 1.000 | 0.080 | 0.080 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.011 | 0.002 | 0.000 | 0.002 | 1 | 5 | 0.239 | 0.005 | 1.000 | 8.399 | 8.401 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.021 | 0.000 | 0.000 | 0.021 | 1 | 5 | 3.714 | 0.012 | 0.922 | 0.006 | 0.006 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.161 | 0.009 | 0.001 | 0.001 | 1 | 1 | 3.759 | 0.006 | 0.929 | 0.309 | 0.309 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.020 | 0.000 | 0.000 | 0.020 | 1 | 1 | 0.240 | 0.004 | 1.000 | 0.083 | 0.083 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.732 | 0.015 | 0.000 | 0.002 | -1 | 1 | 0.240 | 0.004 | 1.000 | 7.228 | 7.229 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.002 | 0.000 | 0.004 | -1 | 1 | 3.727 | 0.022 | 0.922 | 0.001 | 0.001 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.637 | 0.019 | 0.000 | 0.003 | -1 | 5 | 3.774 | 0.017 | 0.896 | 0.699 | 0.699 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.009 | 0.002 | 0.000 | 0.009 | -1 | 5 | 0.239 | 0.004 | 1.000 | 0.038 | 0.038 | See | See |
KNeighborsClassifier_kd_tree¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | ... | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | fe8267e25dadb302ed498e50fabf7ef4 | 1eb6cf1a720a225efb91df0b529b0510 | 0.876317 | 1.276624 | NaN | ... | kd_tree | -1 | 1 | 0.929 | 2.644049 | 0.283099 | 1.000 | 0.331430 | 0.333324 | 0.071 |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | fe8267e25dadb302ed498e50fabf7ef4 | 1eb6cf1a720a225efb91df0b529b0510 | 0.002644 | 0.000434 | NaN | ... | kd_tree | -1 | 1 | 1.000 | 129.771584 | 0.000000 | 0.946 | 0.000020 | 0.000020 | 0.054 |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | dc74b969bf622bc24ba3bc62c980983b | 1eb6cf1a720a225efb91df0b529b0510 | 1.097765 | 0.502636 | NaN | ... | kd_tree | -1 | 5 | 0.946 | 128.980787 | 0.000000 | 0.951 | 0.008511 | 0.008511 | 0.005 |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 41accfcdcd5c50784bedf6164b63de99 | 1eb6cf1a720a225efb91df0b529b0510 | 5.663641 | 0.742520 | NaN | ... | kd_tree | 1 | 100 | 0.951 | 2.630994 | 0.211112 | 1.000 | 2.152662 | 2.159581 | 0.049 |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 41accfcdcd5c50784bedf6164b63de99 | 1eb6cf1a720a225efb91df0b529b0510 | 0.003108 | 0.001076 | NaN | ... | kd_tree | 1 | 100 | 1.000 | 131.848519 | 0.000000 | 0.946 | 0.000024 | 0.000024 | 0.054 |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 022f7445d43bb1dbc24dc3106c03cb93 | 1eb6cf1a720a225efb91df0b529b0510 | 3.071856 | 0.116202 | NaN | ... | kd_tree | -1 | 100 | 0.951 | 133.022136 | 0.000000 | 0.929 | 0.023093 | 0.023093 | 0.022 |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 84622ba45e941db642965553529e1941 | 1eb6cf1a720a225efb91df0b529b0510 | 1.694613 | 0.341814 | NaN | ... | kd_tree | 1 | 5 | 0.946 | 0.005019 | 0.000133 | 1.000 | 337.654977 | 337.774382 | 0.054 |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 84622ba45e941db642965553529e1941 | 1eb6cf1a720a225efb91df0b529b0510 | 0.001532 | 0.000425 | NaN | ... | kd_tree | 1 | 5 | 1.000 | 0.049478 | 0.020856 | 0.911 | 0.030964 | 0.033602 | 0.089 |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | a9455565db1d8e052a783317c99744ff | 1eb6cf1a720a225efb91df0b529b0510 | 0.947502 | 0.346885 | NaN | ... | kd_tree | 1 | 1 | 0.929 | 0.061353 | 0.004726 | 0.894 | 15.443408 | 15.489162 | 0.035 |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | fe8267e25dadb302ed498e50fabf7ef4 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.027441 | 0.020019 | NaN | ... | kd_tree | -1 | 1 | 0.891 | 0.005181 | 0.000274 | 1.000 | 5.296273 | 5.303700 | 0.109 |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | fe8267e25dadb302ed498e50fabf7ef4 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.001961 | 0.000187 | NaN | ... | kd_tree | -1 | 1 | 1.000 | 0.038669 | 0.000424 | 0.911 | 0.050701 | 0.050704 | 0.089 |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | dc74b969bf622bc24ba3bc62c980983b | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.022126 | 0.000991 | NaN | ... | kd_tree | -1 | 5 | 0.911 | 0.038170 | 0.000543 | 0.891 | 0.579682 | 0.579741 | 0.020 |
12 rows × 22 columns
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.028 | 0.029 | 0.026 | 0.0 | -1 | 1 | 131.220 | 0.000 | 0.929 | 0.023 | 0.023 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.635 | 0.078 | 0.022 | 0.0 | -1 | 5 | 2.654 | 0.312 | 1.000 | 1.370 | 1.379 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.588 | 0.084 | 0.022 | 0.0 | 1 | 100 | 133.774 | 0.000 | 0.951 | 0.027 | 0.027 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.617 | 0.111 | 0.022 | 0.0 | -1 | 100 | 2.675 | 0.279 | 1.000 | 1.352 | 1.359 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.642 | 0.060 | 0.022 | 0.0 | 1 | 5 | 0.050 | 0.024 | 0.891 | 73.275 | 81.293 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.630 | 0.062 | 0.022 | 0.0 | 1 | 1 | 0.005 | 0.000 | 1.000 | 720.991 | 721.120 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | 0.017 | 0.0 | -1 | 1 | 0.060 | 0.001 | 0.894 | 0.016 | 0.016 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.032 | 0.0 | -1 | 5 | 0.005 | 0.000 | 1.000 | 0.101 | 0.101 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.876 | 1.277 | 0.000 | 0.001 | -1 | 1 | 2.644 | 0.283 | 1.000 | 0.331 | 0.333 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 1 | 129.772 | 0.000 | 0.946 | 0.000 | 0.000 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.098 | 0.503 | 0.000 | 0.001 | -1 | 5 | 128.981 | 0.000 | 0.951 | 0.009 | 0.009 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 5 | 2.638 | 0.197 | 1.000 | 0.001 | 0.001 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.664 | 0.743 | 0.000 | 0.006 | 1 | 100 | 2.631 | 0.211 | 1.000 | 2.153 | 2.160 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 100 | 131.849 | 0.000 | 0.946 | 0.000 | 0.000 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.072 | 0.116 | 0.000 | 0.003 | -1 | 100 | 133.022 | 0.000 | 0.929 | 0.023 | 0.023 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 100 | 2.685 | 0.327 | 1.000 | 0.002 | 0.002 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.695 | 0.342 | 0.000 | 0.002 | 1 | 5 | 0.005 | 0.000 | 1.000 | 337.655 | 337.774 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 5 | 0.049 | 0.021 | 0.911 | 0.031 | 0.034 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.948 | 0.347 | 0.000 | 0.001 | 1 | 1 | 0.061 | 0.005 | 0.894 | 15.443 | 15.489 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.005 | 0.000 | 1.000 | 0.196 | 0.196 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.027 | 0.020 | 0.001 | 0.000 | -1 | 1 | 0.005 | 0.000 | 1.000 | 5.296 | 5.304 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 1 | 0.039 | 0.000 | 0.911 | 0.051 | 0.051 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.022 | 0.001 | 0.001 | 0.000 | -1 | 5 | 0.038 | 0.001 | 0.891 | 0.580 | 0.580 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 0.005 | 0.000 | 1.000 | 0.383 | 0.383 | See | See |
HistGradientBoostingClassifier_best¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: learning_rate=0.01, n_iter_no_change=10.0, max_leaf_nodes=100.0, max_bins=255.0, min_samples_leaf=100.0, max_iter=300.0.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | ... | max_leaf_nodes | min_samples_leaf | n_iter_no_change | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | HistGradientBoostingClassifier_best | predict | 100000 | 1000 | 100 | 25b9f14bed7dd5d830c6ccd4dfebbf0c | 8c8fffa8ec4b2d8de833421f9e32beab | 0.107042 | 0.000942 | 300 | ... | 100 | 100 | 10 | 0.824 | 0.410986 | 0.00975 | 1.0 | 0.260452 | 0.260525 | 0.176 |
1 rows × 25 columns
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | HistGradientBoostingClassifier_best | fit | 100000 | 100000 | 100 | 93.347 | 0.0 | 300 | 0.001 | 0.001 | 0.501 | 0.021 | 0.824 | 186.379 | 186.541 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | HistGradientBoostingClassifier_best | predict | 100000 | 1000 | 100 | 0.107 | 0.001 | 300 | 0.007 | 0.0 | 0.411 | 0.01 | 1.0 | 0.26 | 0.261 | See | See |